CS329A Self-Improving AI Agents
9 lectures, 10 hr 40 min in all
This playlist contains video recordings of Stanford's graduate-level CS329A course. It covers the latest techniques and applications of AI agents that can continuously improve themselves through interaction with themselves and the environment. The lecture recordings start with self-improvement techniques for LLMs, such as constitutional AI, using verifiers, scaling test-time compute, combining search with LLMs, and train time scaling with RL. The lecture recordings then discuss the latest research in augmenting LLMs with tool use, code, and memory, and orchestrating AI capabilities with multimodal interaction. The lecture recordings next discuss multi-step reasoning and planning problems for agentic workflows, and the challenges in building robust evaluation frameworks.
0 of 9 watched
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
